Reliable and student-friendly, Using IBM® SPSS® Statistics for Research Methods and Social Science Statistics by William E. Wagner, III is known for its effectiveness in helping readers learn to use SPSS software for simple data management. Now reflecting SPSS Version 23.0, the Sixth Edition includes updated examples, screenshots, and tables based on current GSS (General Social Survey) data. This manual is an excellent companion to any undergraduate social statistics and research methods text and is ideal as a stand-alone guide for those learning to use SPSS software for the first time.

CHAPTER 1: Overview

What’s the Difference Between SPSS Statistics and PASW Statistics? None.

Statistical Software

About the GSS Data

SPSS/PASW Electronic Files

Opening Existing Data Files

Importing Data From Statistics File Formats Other Than SPSS or PASW

Opening Previously Created Output Files

Saving Files

Creating New SPSS Statistics Data Files

Creating and Editing SPSS Statistics Output Files

Preferences: Getting Started

Measurement of Variables Using SPSS Statistics

CHAPTER 2: Transforming Variables

Recoding and Computing Variables

Recoding Variables: Dichotomies and Dummy Variables

Recoding Using Two or More Variables to Create a New Variable

Computing Variables

Using the Count Function

Computing an Index Using the Mean

Multiple Response

CHAPTER 3: Selecting and Sampling Cases

Targeted Selection

Random Selection

Selecting Cases for Inclusion in a New Data Set

CHAPTER 4: Organization and Presentation of Information

Measures of Central Tendency and Variability

Frequency Distributions

CHAPTER 5: Charts and Graphs

Boxplot

Legacy Options for Graphs (Boxplot Example)

Scatterplot

Legacy Scatterplot

Histogram

Multivariate Histogram

Horizontal Histogram

Bar Graph

Multivariate Bar Graph

Pie Chart

Additional Graphic Capabilities in SPSS Statistics

CHAPTER 6: Testing Hypotheses Using Means and Cross-Tabulation

Comparing Means

Comparing Means: Paired-Samples t Test

Comparing Means: Independent-Samples t Test

One-Sample t Test

Chi-Square

Chi-Square and Cross-Tabulation

CHAPTER 7: Cross-Tabulation and Measures of Association for Nominal and Ordinal Variables

Bivariate Analysis

Adding Another Variable or Dimension to the Analysis

Measures of Association for Nominal and Ordinal Variables

Lambda

Gamma, Kendall’s Tau-b, and Somers’ d

CHAPTER 8: Correlation and Regression Analysis

Bivariate Regression

Correlation

Multiple Regression

CHAPTER 9: Logistic Regression Analysis

Preparing Variables for Use in Logistic Regression Analysis

Creating a Set of Dummy Variables to Represent a Multicategory Nominal Variable

Logistic Regression Analysis

Logistic Regression Using a Categorical Covariate Without Dummy Variables